Sales Engineer

Cooper

San Francisco (CA)

On-site

USD 150,000 - 200,000

Full time

14 days+

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Benefits offered by this job

Competitive salary & equity

Medical, dental & vision insurance

Monthly wellness stipend

401k with company match

Unlimited PTO

Company sponsored lunch 5x per week

Job summary

Cooper is seeking a Sales Engineer in San Francisco to own the intersection of Sales, Product, and brokerage customer deployments. You’ll write Python, own the agent skill architecture, validate integrations end-to-end, and balance hands-on execution with structured thinking.

Ideal candidates have 3+ years in a technical, customer-facing role at a B2B SaaS company, strong API and integration experience, and comfort working with AI-native workflows.

Qualifications

3+ years in a technical customer-facing role at a B2B SaaS company or similar
Experience translating customer workflows into deployable integrations
Proficiency in Python and building end-to-end integrations

Responsibilities

Partner with Sales to design and deploy customer pilots
Write Python scripts and define the skill architecture for deployments
Configure integrations across customers’ tech stacks (AMS, CRMs, data sources)
Lead deployments end-to-end from discovery to activation
Provide technical enablement and drive adoption with customers
Refine deployment playbooks for repeatable customer wins

Skills

Python scripting

LLM agent workflows

Technical customer-facing

Cross-functional collaboration

Clear technical communication

Tools

AMS

Carrier Portals

CRMs

APIs

Job description

About Cooper AI

Cooper is an AI coworker for the insurance industry. Getting a business insured involves mountains of paperwork: filling out repetitive forms, re‑typing the same information into one insurance company’s website after another, and comparing offers by hand. Cooper does that busywork automatically, right inside the tools people already use, so brokers and their teams can focus on advising clients instead of pushing paper. We’re a small team with deep insurance roots, teaching AI to do real, trusted work in a massive, overlooked industry. Backed by Lightspeed, General Catalyst, and Valor, Cooper AI is building from the ground up to modernize a $1T+ global insurance industry.

About The Role

As our Sales Engineer, you’ll own the intersection of Sales, Product, and our brokerage customers, shaping how we sell, deploy, and drive value from Cooper’s AI platform. This is a highly technical, customer‑facing role: you’ll write Python, own the skill architecture behind every customer’s agent, validate integrations end‑to‑end, and run tight loops between users, Product, and Engineering. It’s the role for engineers who thrive in ambiguity and balance hands‑on execution with structured thinking.

What You’ll Do

Partner with Sales to design and deploy customer pilots that prove Cooper’s value to prospects
Translate insurance workflows into agent resources: write extensible Python scripts, author skills and own the technical architecture for every customer deployment
Configure integrations across customers’ technology stacks e.g., AMS & CRMs, Carrier Portals, and data sources
Run tight feedback loops between Sales, Product, and Engineering, turning live customer signal into roadmap influence
Lead deployments end‑to‑end from technical discovery through activation, serving as a trusted technical partner who drives user enablement and adoption
Shape and refine the deployment playbook so every customer win compounds into leverage for the next

What you’ll bring

3+ years of relevant experience in a technical customer‑facing role at a B2B SaaS company ideally as a sales engineer, solutions engineer, or forward‑deployed engineer (similar enterprise AI/SaaS deployment backgrounds also welcome)
Outcome ownership: Track record driving multi‑stakeholder implementations to go‑live
Python proficiency: Skilled with automation and custom scripting, deep understanding of APIs, and able to design and deploy end‑to‑end integrations that solve complex business workflows
AI‑native: Comfortable building with coding agents like Claude Code/Cursor etc. Experience building with LLMs and designing autonomous agent workflows is a significant advantage
Strong communication: Connects business problems to Cooper’s solutions for technical and non‑technical audiences alike.
Bias for action with high EQ: Represents the buyer in a leadership meeting and debugs with a frustrated CSR the same afternoonComfort with ambiguity: Shapes solutions as much as you implement them; defaults to first‑principles thinking

Preferred Qualifications